Langchain-Chatchat/configs/prompt_config.py.example

# prompt模板使用Jinja2语法，简单点就是用双大括号代替f-string的单大括号
# 本配置文件支持热加载，修改prompt模板后无需重启服务。


# LLM对话支持的变量：
#   - input: 用户输入内容

# 知识库和搜索引擎对话支持的变量：
#   - context: 从检索结果拼接的知识文本
#   - question: 用户提出的问题

# Agent对话支持的变量：

#   - tools: 可用的工具列表
#   - tool_names: 可用的工具名称列表
#   - history: 用户和Agent的对话历史
#   - input: 用户输入内容
#   - agent_scratchpad: Agent的思维记录

PROMPT_TEMPLATES = {}

PROMPT_TEMPLATES["llm_chat"] = {
"default": "{{ input }}",
"with_history":
"""The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.

Current conversation:
{history}
Human: {input}
AI:""",
"py":
"""
你是一个聪明的代码助手，请你给我写出简单的py代码。 \n
{{ input }}
""",
}

PROMPT_TEMPLATES["knowledge_base_chat"] = {
"default":
"""
<指令>根据已知信息，简洁和专业的来回答问题。如果无法从中得到答案，请说 “根据已知信息无法回答该问题”，不允许在答案中添加编造成分，答案请使用中文。 </指令>
<已知信息>{{ context }}</已知信息>、
<问题>{{ question }}</问题>
""",
"text":
"""
<指令>根据已知信息，简洁和专业的来回答问题。如果无法从中得到答案，请说 “根据已知信息无法回答该问题”，答案请使用中文。 </指令>
<已知信息>{{ context }}</已知信息>、
<问题>{{ question }}</问题>
""",
"Empty":  # 搜不到知识库的时候使用
"""
请你回答我的问题:
{{ question }}
\n
""",
}
PROMPT_TEMPLATES["search_engine_chat"] = {
"default":
"""
<指令>这是我搜索到的互联网信息，请你根据这些信息进行提取并有调理，简洁的回答问题。如果无法从中得到答案，请说 “无法搜索到能回答问题的内容”。 </指令>
<已知信息>{{ context }}</已知信息>
<问题>{{ question }}</问题>
""",
"search":
"""
<指令>根据已知信息，简洁和专业的来回答问题。如果无法从中得到答案，请说 “根据已知信息无法回答该问题”，答案请使用中文。 </指令>
<已知信息>{{ context }}</已知信息>、
<问题>{{ question }}</问题>
""",
}
PROMPT_TEMPLATES["agent_chat"] = {
"default":
"""
Answer the following questions as best you can. If it is in order, you can use some tools appropriately.You have access to the following tools:

{tools}

Please note that the "知识库查询工具" is information about the "西交利物浦大学" ,and if a question is asked about it, you must answer with the knowledge base，
Please note that the "天气查询工具" can only be used once since Question begin.

Use the following format:
Question: the input question you must answer1
Thought: you should always think about what to do and what tools to use.
Action: the action to take, should be one of [{tool_names}]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can be repeated zero or more times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin!

history: {history}

Question: {input}

Thought: {agent_scratchpad}
""",

"ChatGLM3":
"""
You can answer using the tools, or answer directly using your knowledge without using the tools.Respond to the human as helpfully and accurately as possible.
You have access to the following tools:
{tools}
Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
Valid "action" values: "Final Answer" or  [{tool_names}]
Provide only ONE action per $JSON_BLOB, as shown:

```
{{{{
  "action": $TOOL_NAME,
  "action_input": $INPUT
}}}}
```

Follow this format:

Question: input question to answer
Thought: consider previous and subsequent steps
Action:
```
$JSON_BLOB
```
Observation: action result
... (repeat Thought/Action/Observation N times)
Thought: I know what to respond
Action:
```
{{{{
  "action": "Final Answer",
  "action_input": "Final response to human"
}}}}
Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.

history: {history}

Question: {input}

Thought: {agent_scratchpad}
""",
}